Identifying degraded lands and degradation trends is essential to determine measures that contribute to avoiding, reducing, and reversing the rate of deterioration of natural resources. In this study, we assessed the state and trend of degradation in Ixtacamaxtitlan, Puebla, Mexico, by determining the spatial and temporal changes of three indicators, Land Cover (LC), Land Productivity Dynamics (LPD), and Soil Organic Carbon (SOC), during the period 2000–2015, using global data proposed by the Convention to Combat Desertification for the implementation of Land Degradation Neutrality (LDN). The results showed increases in croplands (6.89%) and a reduction in grasslands (9.09%), with this being the transition that presents the most significant extension in the territory. The LPD is the indicator where the most deterioration was observed, and due to negative changes in LC, SOC losses were estimated at more than 7000 tons in the study period. The proportion of degraded land was 19% of approximately 567.68 km² of Ixtacamaxtitlan’s surface. Although the municipality presents incipient degradation and only a tiny part showed improvement, identifying areas with degradation processes in this work will favor degradation monitoring and the adequate planning and application of restoration measures in the local context to promote the path towards LDN.

Transitional waters (TWs) are relevant ecological and economical ecosystems that include estuaries, deltas, bays, wetlands, marshes, coastal lakes, and coastal lagoons and play a central role in providing food, protecting coastal environments, and regulating nutrients. However, human activities such as industrialization, urbanization, tourism, and agriculture are threatening these ecosystems, which results in contamination and habitat degradation. Therefore, it is essential to evaluate contamination in TW to develop effective management and protection strategies. This study analyses the application of geospatial technologies (GTS) for monitoring and predicting contaminant distribution in TW. Cartography, interpolation, complex spatial methods, and remote sensing were applied to assess contamination profiles by heavy metals, and persistent organic compounds, and analyze contamination indices or some physicochemical water parameters. It is concluded that integrating environmental and demographic data with GTS would help to identify critical points of contamination and promote ecosystem resilience to ensure long-term health and human well-being. This review comprehensively analyzes the methods, indicators, and indices used to assess contamination in transitional waters in conjunction with GTS. It offers a valuable foundation for planning future research on pollution in these types of waters or other similar water bodies worldwide.

The Alto Atoyac Basin (AAB) in central Mexico is one of the most environmentally degraded regions in the country. This review systematically compiles 60 peer-reviewed studies on environmental contamination from 1975 to 2024. A unified, standardized database supported spatial and temporal analyses using GIS and non-parametric tests, revealing pollution hotspots and disparities in monitoring coverage. Spatial analysis showed a high concentration of studies along the Atoyac River, while nineteen municipalities lacked any records. Research primarily focused on surface water and sediments, with limited attention given to groundwater, soils, air, and food matrices. Data on human exposure remains scarce and fragmented, limiting risk assessment. The evidence reveals widespread contamination linked to industrial, urban, and agricultural pressures. Detected pollutants include pathogens, heavy metals, and diverse organic compounds exceeding national and international thresholds. Spatial analysis highlights pollutant concentrations in densely populated and industrialized zones, while temporal patterns show ongoing degradation from continuous discharges and limited remediation efforts. The findings emphasize long-term ecological degradation and potential health risks, underscoring the need for integrated monitoring and spatially informed management to guide recovery and policy actions. Future efforts should focus on continuous monitoring, multivariate and spatial modeling, and integrated basin-management frameworks to support restoration in the AAB.

Forests play an essential role in climate change as they are the terrestrial ecosystems that store the highest C content in their soils and biomass. Despite this, the lack of information at the subnational level hinders their proper management and conservation. This study aimed to identify the extension and distribution of forests and to develop an empirical model for the spatial prediction of soil organic matter (SOM) in Ixtacamaxtitlan, Puebla, Mexico, based on environmental variables generated through Geographical Information Systems. A supervised classification in Landsat 8 images was used to define the forest cover, and environmental variables related to topography, climate and vegetation were generated. Finally, a Multiple Linear Regression model validated with the leave-one-out cross-validation method was used to examine the relationships between the covariates and the SOM and estimate its content in forest. The results show that the forest cover extension is 41%, with an overall accuracy of 97.7%. The model shows a good fit (R²_cv = 0.69, RMSE_cv = 1.53). The mean of SOM was 5.2%, and upper values were consistent with higher altitude, precipitation and cooler temperature. Estimating SOM content in forest areas is essential in developing planning strategies at the subnational level to mitigate the harmful effects of climate change.

La determinación de cambios en la cubierta terrestre (CT) es importante para entender la dinámica de los ecosistemas. En este estudio se analizaron los cambios espaciales y temporales en el municipio de Ixtacamaxtitlán, Puebla durante el periodo 2000-2015, utilizando los mapas globales de la Agencia Espacial Europea ESA-CCI-LC. Para ello, se determinó la matriz de cambios, la tasa anual de cambio y la probabilidad de permanencia, así como la precisión del mapa de CT 2015. Los resultados indican que las pérdidas se concentraron en las coberturas arboladas y pastizales (0.27% y 8.83%, respectivamente), mientras que las ganancias se dieron en tierras de cultivo y zonas urbanas (6.9% y 8.11%, respectivamente). La mayoría de los cambios se observaron en las zonas de fácil acceso ubicadas en la porción centro-norte del municipio. De las 1962 ha que presentaron cambios entre categorías, en 87.4% el cambio fue negativo y en 12.6% fue positivo, destacando la transición de pastizales y superficies arboladas hacia tierras de cultivo, causadas por diversos procesos socioeconómicos presentes en la zona como marginación, migración, acceso a programas gubernamentales, expansión de áreas agrícolas y diversificación de cultivo. El mapa de CT 2015 mostró una alta precisión a escala subnacional (85.64%) lo que revela que este conjunto de datos es confiable para el estudio de las transformaciones en el territorio.

Los Sistemas de Información Geográfica (SIG) son herramientas clave para el análisis y visualización de datos geoespaciales, permitiendo capturar, almacenar, analizar y mostrar información geográficamente referenciada. Los SIG están compuestos por hardware, software, datos geoespaciales, metodologías y usuarios capacitados para su manejo. Estos sistemas permiten una amplia gama de aplicaciones que dependen de sus objetivos de uso como la navegación, el turismo, la construcción y el comercio. En el ámbito socioambiental, los SIG son cruciales para la planificación territorial, el análisis de riesgos y la gestión de los recursos naturales y la biodiversidad. Facilitan el análisis de fenómenos como el cambio climático, la contaminación y la distribución de enfermedades y además, permiten el análisis de la exposición a contaminantes y sus impactos en la salud pública, proporcionando una comprensión más profunda de la relación entre el entorno y las actividades humanas. Su capacidad para adaptar aplicaciones a diversos objetivos los convierte en una herramienta invaluable para la toma de decisiones informadas y en la implementación de intervenciones efectivas.